1. Field of the Invention
The present invention relates to a multimedia retrieval system, and more particularly, to an image retrieval method and apparatus using iterative matching in order to improve accuracy of retrieval without overload of retrieval time in a content-based image retrieval system.
2. Description of the Related Art
Recently in the content-based multimedia retrieval trend, the focus has been put on providing a user-friendly interface with overcoming the limitation of keyword retrieval in text-based retrieval. Particularly, the rapid growth of the Internet, personalization of multimedia equipment, and the introduction of digital libraries have been stimulating demands for content-based multimedia retrieval. Meanwhile, the content-based image retrieval includes analyzing image characteristic information such as colors, textures, shapes and faces and arranging images which are visually the more similar to a desired image, in order of visual similarity. Content-based image retrieval comprises a step for extracting characteristics and a step for image matching. In the step for extracting characteristics, predetermined vectors are extracted to describe the characteristics of an image and all images are expressed by respective characteristic vectors and stored in a predetermined database. In the step for image matching, if a query image is given, similarities between the query image and the images in the database are calculated in a characteristic vector domain, and the images in the database are arranged in order of the calculated similarity to the query image.
Many methods related to characteristics extracting and image matching have been under development. For the characteristics extracting among the methods, a variety of characteristic descriptors are being developed particularly in an MPEG-7 category. Meanwhile, for the image matching, methods for reducing a search time and fusion of a plurality of characteristics are mainly being studied. For example, among related research articles, there are “Hierarchical Discriminant Regression,” by W. Hwang and J. Weng, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 11, November 2000, pp. 1277-1293, and “Automatic Query Generation for Content-Based Image Retriever,” by C. Breitneder and H. Eidenberger, IEEE Conference on Multimedia and Expo, Jul. 30-Aug. 2, 2000, vol. 2, pp. 705-708.
However, though many methods have been tried to reduce a search time or to efficiently fuse a variety of characteristics in the image matching step in the prior art as in the above articles, efforts to improve accuracy of the matching based on knowledge have not been made yet. Accordingly, when an image is retrieved by the above methods, since major characteristic information items of images being determined to be similar are all different, the result is not satisfying sometimes. In addition, even though images have identical contents, changes of illumination or poses can cause different characteristic information items on colors or textures to be stored such that an image may not be retrieved accurately.
To solve these problems, there is a method by which a user feeds information on images similar to a desired image back to a retrieval apparatus by using the result of a first retrieval, so that the retrieval apparatus automatically calculates what is a more important characteristic information item and as a result carries out retrieval again by increasing the weighted value of the important characteristic information item. However, if the retrieval is carried out again, all images stored in an image database used in the first retrieval should be retrieved such that calculation of similarities between the query image and stored images becomes more complicated and if the frequency of iteration increases in order to improve retrieval performance, the burden to the retrieval engine also increases.